a[sdp+1] = sdp_vals
return a
def process(doc, filt):
ds = doc.getElements("Data", depth=1)[0]
dat = ds.getData()
dat[:,1] = cal._applyfilter(dat[:,1], filt)
dat[:,0] = smooth(dat[:,0])
if __name__ == '__main__':
mff=os.path.join(os.path.split(ftt.__file__)[0], 'MicroflownCalib.ncl')
fd = io.read(mff)
filt = fd.getElements('Data')[0]
filt = cal._filterResample(filt.data[:,0], filt.fs(), SIGFS)
for dname in sys.argv[1:]:
dname = dname.strip("/")
if os.path.isfile(os.path.join(dname, 'concat_ex.mdat')):
ifn = os.path.join(dname, 'concat_ex.mdat')
ofn = dname+"_sin.mdat"
doc = io.read(ifn)
print("Handling %s" % ifn)
process(doc, filt)
io.write(doc, ofn)
if os.path.isfile(os.path.join(dname, 'concat.mdat')):
ifn = os.path.join(dname, 'concat.mdat')
ofn = dname+"_all.mdat"
doc = io.read(ifn)
print("Handling %s" % ifn)
import mien.parsers.fileIO as io
import mien.nmpml.data as miendata
import mien.parsers.nmpml as nmpml
from mien.datafiles.dataset import resample, crop
import gicaos.fttools as ftt
import gicmext.calibration as cal
import gicaos.constructTransferFunctions as ctf
SIGFS = 1000
TRIGCHAN = 4
MFCHAN = 2
MFF=os.path.join(os.path.split(ftt.__file__)[0], 'MicroflownCalib.ncl')
MFF= io.read(MFF)
MFF= MFF.getElements('Data')[0]
MFF= cal._filterResample(MFF.data[:,0], MFF.fs(), SIGFS)
def smooth(a,fs):
#find clicks
ad = a[1:]-a[:-1]
adm = ad.mean()
adv = ad.std()
cd = nonzero(abs(ad) > abs(adm) + 4*adv)[0] # FREE PARAMETER HERE
# each 1 time point click is associated with 2 entries in cd, k and k+1
# each 2 pt time click is associated with 2 entries in cd, k and k+2
# replace clicks with averages
c=0;
clicks=0;
for k in cd:
c=c+1
if (k== cd[0]) or ( (k < cd[-1]) and (k-cd[c-2] > 2) and (cd[c] - k ==1) ) or ( (k == cd[-1]) and (k-cd[c-2] > 2) ):
